class_docstr: Construct an MBART tokenizer.
  
  Adapted from [`RobertaTokenizer`] and [`XLNetTokenizer`]. Based on
  [SentencePiece](https://github.com/google/sentencepiece).
  
  The tokenization method is `<tokens> <eos> <language code>` for source language documents, and `<language code>
  <tokens> <eos>` for target language documents.
  
  Examples:
  
  ```python
  >>> from transformers import MBartTokenizer
  
  >>> tokenizer = MBartTokenizer.from_pretrained("facebook/mbart-large-en-ro", src_lang="en_XX", tgt_lang="ro_RO")
  >>> example_english_phrase = " UN Chief Says There Is No Military Solution in Syria"
  >>> expected_translation_romanian = "Şeful ONU declară că nu există o soluţie militară în Siria"
  >>> inputs = tokenizer(example_english_phrase, text_target=expected_translation_romanian, return_tensors="pt")
  ```
docstr: Create a mask from the two sequences passed to be used in a sequence-pair classification task. mBART does not
  make use of token type ids, therefore a list of zeros is returned.
  
  Args:
      token_ids_0 (`List[int]`):
          List of IDs.
      token_ids_1 (`List[int]`, *optional*):
          Optional second list of IDs for sequence pairs.
  
  Returns:
      `List[int]`: List of zeros.
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code: def create_token_type_ids_from_sequences(
      self,
      token_ids_0: List[int],
      token_ids_1: Optional[List[int]] = None,
  ) -> List[int]:
      """
      Create a mask from the two sequences passed to be used in a sequence-pair classification task. mBART does not
      make use of token type ids, therefore a list of zeros is returned.
  
      Args:
          token_ids_0 (`List[int]`):
              List of IDs.
          token_ids_1 (`List[int]`, *optional*):
              Optional second list of IDs for sequence pairs.
  
      Returns:
          `List[int]`: List of zeros.
  
      """
  
      sep = [self.sep_token_id]
      cls = [self.cls_token_id]
  
      if token_ids_1 is None:
          return len(cls + token_ids_0 + sep) * [0]
      return len(cls + token_ids_0 + sep + sep + token_ids_1 + sep) * [
          0
      ]
  
imports: import os
  from shutil import copyfile
  from typing import Any, Dict, List, Optional, Tuple
  import sentencepiece
  from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
  from ...utils import logging
label_desc: Use image node_id 9 for calling the MBartTokenizer obj's underlying member method code with example usage: obj.create_token_type_ids_from_sequences(token_ids_0, token_ids_1) and returns: unknown, unknown